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Abstract:

Directional albedo of a particular article, such as an identity card, is
measured and stored. When the article is later presented, it can be
confirmed to be the same particular article by re-measuring the albedo
function, and checking for correspondence against the earlier-stored
data. The re-measuring can be performed through us of a handheld optical
device, such as a camera-equipped cell phone. The albedo function can
serve as random key data in a variety of cryptographic applications. The
function can be changed during the life of the article. A variety of
other features are also detailed.

Claims:

1-8. (canceled)

9. A method comprising: capturing image data from an object using a 2D
sensor; estimating a relative position between said object and said
sensor; by reference to data previously acquired and stored in a data
structure, obtaining a set of data that should correspond to image data
captured from said object from said relative position; and checking said
captured image data and said obtained set of data for correlation.

10. A method comprising: capturing plural views of a reference object,
each from a different perspective; storing data corresponding to the
foregoing; subsequently capturing plural views from a second object, each
from a different perspective; identifying a subset of the stored data
corresponding to the perspectives from which views of the second object
were subsequently captured; and by reference to said subset, and said
subsequently-captured views, determining whether the second object is the
reference object.

11. The method of claim 10 that includes: determining a first directional
albedo function by reference to the subsequently captured views from the
second object; determining a second albedo function by reference to the
identified subset of stored data; and performing a correlation operation
between said first and second albedo functions.

12. The method of claim 11 that includes: determining a third albedo
function by reference to a complete set of said stored data; comparing
said second and third albedo functions to determine elements thereof that
diverge by more than a threshold.

13. The method of claim 12 that includes disregarding said determined
elements when performing a correlation between the first and second
albedo functions.

14. The method of claim 11 that includes: determining a third albedo
function by reference to a complete set of said stored data; comparing
said second and third albedo functions to determine elements thereof that
match within a threshold.

15. The method of claim 14 that includes disregarding said determined
elements when performing a correlation between the first and second
albedo functions.

16. A method of checking authenticity of a printed article, the article
conveying hidden data, the method including capturing image data from the
article using an imager in a handheld communications device such as a
camera-equipped mobile phone, and detecting the hidden data from the
captured image data, the method further characterized by generating an
audio output comprised of plural audible components, wherein the audible
components are dependent on the detected hidden data, so that a user can
recognize an authentic article by recognizing a characteristic audio
output corresponding thereto.

17. The method of claim 16 wherein the printed article conveys plural
different hidden data, and the method includes moving the article
relative to the imager, wherein different of said plural hidden data are
detected at different times, causing different of said audible components
to be generated during the course of said movement.

19. The method of claim 16 wherein the article conveys two
distinctly-encoded hidden data, the first of said data being represented
by colored print that is out-of-gamut for RGB printing, so that same is
not accurately reproduced in an RGB-printed copy of the article, and
wherein the method includes detecting said two distinctly-encoded hidden
data, and processing same to generate the audible output.

20. The method of claim 19 that includes checking the two
distinctly-encoded hidden data for correlation, and generating the audio
output based thereon.

21. The method of claim 19 wherein the second of said data comprises
directional albedo data.

22. The method of claim 19 that includes detecting both of said
distinctly-encoded hidden data from the captured image data.

23. The method of claim 16 wherein the article conveys first and second
hidden data, and the method includes determining orientation of the
article by reference to the first hidden data; using the determined
orientation in detecting the second hidden data; and processing the
second hidden data to generate the audible output.

[0002] The technology detailed herein relates--in certain aspects--to
sensing optical data from an object, and uses of the resulting data.

BACKGROUND

[0003] The following references detail technologies applicable in
connection with applicants' work.

[0004] U.S. Pat. No. 6,584,214 discloses how three-dimensional
characteristics of a complex physical structure can be used to generate a
unique identifier useful, e.g., in cryptography. In effect, the physical
characteristics represent the basis of a "physical one-way hash function"
that facilitates derivation of an identifier based on the structure (yet
the structure cannot be reproduced given only the identifier).

[0005] Related work is detailed in the March, 2001, MIT thesis by Pappu,
entitled "Physical One-Way Functions," and in the related Pappu et al
paper of the same name, published in the Sep. 20, 2002, issue of Science
(Vol. 297, pp. 2026-2030). Chen et al have noted that an inexpensive
physical object can serve as a cryptographic element, if a random unique
structure of the object (e.g., paper fiber) is accurately quantified.
("Certifying Authenticity via Fiber-Infused Paper," ACM SIGecom
Exchanges, Volume 5, Issue 3, April 2005, pages 29-37.)

[0006] Rodriguez et al have written about use of cell phones and like
devices for validation of document security features. ("On the Use of
Mobile Imaging Devices for the Validation of First- and Second-Line
Security Features," SPIE Vol. 6075, February, 2006.)

[0007] WIPO patent publication WO 2005/106783 details how the propagation
of sonic vibrations through an inhomogeneous medium--such as a card with
embedded irregularities--can generate data by which the medium can be
uniquely identified.

[0008] A number of patent documents teach how a medium can be uniquely
identified by reference to its inherent physical characteristics, such
microscopic grain structure, optical characteristics, or structural
characteristics. Examples include US20050190914, US20050210255,
US20030035564, US20050262350, WO0065541, WO03030105 (corresponding, e.g.,
to U.S. applications 60/317,665, and 60/394,914), and WO03087991
(corresponding, e.g., to 60/371,073).

[0009] Arrangements in which data is represented by reference to angles
(e.g., angular symbologies) are taught, e.g., in US2003026448 and
US20050285761.

[0011] U.S. Pat. No. 6,421,453 shows that gestures can be employed in
identification applications.

[0012] To provide a comprehensive disclosure without unduly lengthening
this specification, the documents identified herein (both above and
below) are incorporated by reference.

DISCUSSION

[0013] The term "secure document" conjures various concepts to the
artisan, generally characterized by expensive production materials and
machinery. Examples include currency formed on commercially unobtainable
paper and intaglio-engraved with elaborate guilloche patterns, and driver
licenses incorporating sophisticated laminates and myriad other
anti-counterfeiting technologies.

[0014] More generally, however, a secure document is simply one that
essentially cannot be duplicated.

[0015] Contrary to familiar notions, in one sense all documents are
secure. At an atomic level, no document can be "duplicated." If, e.g., an
original driver license could be atomically characterized at the time of
its issuance, and the resulting massive data set stored, then this stored
data could later be used as a reference to determine whether a suspect
license is the original one, or an imperfect forgery.

[0016] A system built on such principles is, of course, impractical. One
hurdle is to characterize the license--at the time of its issuance--at
the atomic level. If such equipment existed, it would be extraordinarily
expensive. A second hurdle is more confounding: similar equipment would
have to be installed at every reader location (retail outlet, airline
check-in, police cruiser, etc) at which authenticity of the license is to
be assessed.

[0017] However, the insight that every document (indeed, every tangible
article) is irreproducible at some level, allows for some interesting
inquiries.

[0018] For example, how much data must be collected from an article to
permit it to be distinguished from seemingly identical articles (e.g.,
articles produced sequentially using the same manufacturing equipment and
using same source of raw materials)? Can sufficient data be collected
optically, or is resort to characterizing other physical properties
(chemical composition, mechanical features) required?

[0019] Consider an ID card, measuring 3.5''×2.'' If optically
scanned at the time of its issuance using a 600 dpi scanner, it produces
360,000 samples over each square inch. If each sample is composed of 12
bits of red information, 12 bits of blue information, and 12 bits of
green information, the scanning process yield 12,960,000 bits for each
square inch, or 90,720,000 bits across the face of the card. This data
could be stored and used as a check to determine whether a suspect card
is the original. Yet experience suggests that this nearly 100 megabit
data set is not sufficiently detailed for such card authentication. A
counterfeiter with such a scanner and a decent printer could produce a
forged card that cannot be reliably distinguished from the original
(using traditional techniques) by reference to this 100 megabit data set
(taking into account a margin of natural variability associated with
scanner noise and other factors, i.e., the same scanner, scanning the
same article twice in succession, does not produce two identical data
sets, e.g., due to shot noise and other phenomena; ultimately, a
formalized Bayesian decision and/or digital hash comparison process can
better define the word "distinguish" in a practical setting, but for the
purposes of this general introduction, this word is sufficient).

[0020] Higher resolution scanning might be employed to generate a still
larger set of characterization data, but the associated costs of
deploying high resolution scanners to a large number of reading stations
soon makes such approaches impractical. Moreover, as scanning resolution
is increased, it becomes increasingly difficult to determine whether a
difference in data sets is due to different cards, or something as simple
as scanner noise.

[0021] Thus, flat-scan optical characterization of the spectral density of
a card or document does not appear sufficient; resort to other physical
properties--and their precise characterization would appear to be
required.

[0022] Or so it would seem.

[0023] Actually, the desired results may be achieved by counter-intuitive
approaches. For example, instead of looking more closely at a suspect
card--look at it from further away. Likewise, instead of examining the
card under tightly controlled measurement conditions, sense it in a
largely uncontrolled environment. And, to top things off, use a simple
optical sensor. (What first appears like a recipe for disaster might
instead be the seeds for success.)

[0024] In accordance with one aspect of the technology detailed herein, a
simple optical sensor is used to capture sufficient data from a card to
uniquely distinguish the card from another, even if both cards are
designed to be identical, and are produced sequentially from the same
machine.

[0026]FIG. 2 shows the card of FIG. 1, with another geometrical reference
system (x, y, z, wobble angle, and azimuth angle), and showing how a
centroid of reflection for different a-pels on the surface of card is not
always oriented along the z-axis, but rather typically wobbles, e.g.,
over a range of 0-20 degrees, and over a different azimuth angles.

[0027]FIG. 3 is a schematic section view (passing through depicted y-axis
in FIG. 1) showing part of an apparatus 20 for capturing card image data
from different directions, at the time of card production.

[0031]FIG. 7 is a flow chart outlining an illustrative technique for
characterizing a card's 2D albedo map at the time of card production.

[0032]FIG. 8 is a block diagram of a reader station 30, with a card being
waved in front of a webcam.

[0033] FIGS. 9A-C, and 10A-C, show successive frames of how a card might
be viewed by an optical sensor at a reader station, when the card is
waved before the sensor by a user.

[0034]FIG. 11 is a flow chart outline one illustrative technique for
estimating a card's 2D albedo map at a reader station.

[0035] FIGS. 12A and 12B show plots detailing a "wave" of a card in front
of a web cam sensor.

[0036] FIG. 13 shows how microdroplets of thermoplastic resin on a driver
license laminate may be heated by an obliquely applied laser source,
applied from different directions, to reshape the laminate surface, and
thus the license's albedo function.

DETAILED DESCRIPTION

[0037] For expository convenience, the following specification focuses on
driver licenses. However, it should be understand that the principles
herein can be used with tangible articles of any time (e.g., passports,
paper currency, birth certificates, legal documents, medical records,
computer storage media, etc.).

[0038]FIG. 1 shows the top face of a driver license 10, and one
geometrical frame of reference with which certain of the features
detailed below may be described.

[0039] Also shown in FIG. 1, in the lower left corner, are "a-pels" 12a,
12b, 12c ("albedo picture elements") that may be imagined as extending
across the face of the card. These a-pels each correspond to an excerpt
of the card face as sensed by an imaging system. (For clarity's sake, the
a-pels are not to scale. They might more realistically be on the order of
0.1 or 1.0 millimeters on a side, or somewhere under 1,000 to over
100,000 a-pels per square inch of card surface.)

[0040] In a gross sense, generally flat surfaces typically exhibit a
Lambertian reflectivity profile as a function of viewing angle toward
that surface. That is, the maximum reflection of light from the surface
occurs along the axis perpendicular to the surface (i.e., axis z in FIG.
1). However, if examined in more detail (e.g., on a per a-pel basis), it
is found that the angle of maximum reflectivity typically diverges
somewhat from this ideal. This divergence--shown as a "wobble" angle in
FIG. 2, may be on the order of a few tenths of a degree in certain
materials, but on the order of several degrees, or several tens of
degrees, in other materials. (The porcupine is a rough analogy, with
quills pointing in different directions.)

[0041] This direction at which light maximally reflects from an a-pel may
be characterized by the wobble angle (i.e., the divergence from the z
axis), and also by azimuth. Azimuth--measured within the plane of the
card--may be regarded as the direction towards which the
maximally-reflected light "leans."

[0042] In FIG. 2, the direction of maximum reflectivity for each a-pel is
shown by a bold vector (arrow) 11. The grey arrow 13 beneath is a
projection of the vector 11 onto the card's surface, and indicates the
azimuth angle for each vector. As can be seen, the reflectivity vectors
11 associated with different a-pels in FIG. 2 have generally random
wobble and azimuth angles.

[0043] Collectively, the reflectivity vectors 11 shown in FIG. 2 are
essentially unique to any item. Like a fingerprint, they can be used to
characterize the item, and distinguish it from all others (even "copies"
that appear on close inspection--using classic flat-bed scanning or
single-direction viewing--to be identical).

[0044] In addition to having wobble and azimuth angles, each of the
vectors 11 in FIG. 2 is also characterized by length. The length of each
vector indicates the magnitude of light reflected from a corresponding
a-pel. The magnitude of reflected light can be a function of several
factors. One prominent factor is the color of the surface: an a-pel that
is substantially white reflects more light than a a-pel that is
substantially black. When a flatbed scanner, or a camera, images an
object, the pixel data that it captures, generally speaking, is an array
of a-pel magnitude data.

[0045] A scanner or camera does not capture data from which, e.g., wobble
or azimuth angles can be determined. Thus, in optically characterizing a
card, a scanner captures only one dimension of data: magnitude data. Two
further dimensions of independent data--wobble angle and azimuth
angle--are ignored. By paying attention to these further dimensions of
data, exponentially-improved abilities to identify an item--and
distinguish it from others--are achieved. (A three-dimensional cylinder,
viewed in only two dimensions, may appear as a rectangle, a circle, an
ellipse, or a more complex shape--depending on the two-dimensional plane.
Such ambiguities are easily resolved by increasing the dimension by one.
Here the dimension can be increased by two.)

[0046] A first task, then, is to capture the multi-dimensional data that
characterizes the card. FIG. 3 shows part of an apparatus 20 for doing
so.

[0047] Apparatus 20 comprises an array of cameras 14 disposed above a card
10. The card may be placed on a stage, or it may be held in position by a
pick-and-place robot system.

[0048] Each camera 14 includes a lens 16, and a 2D image sensor 18. The
image sensors may comprise, e.g., 1-5 megapixel CCD or CMOS sensors, as
are customarily used in digital cameras.

[0049] The cameras are spaced at known locations relative to the card. In
the sectional view of FIG. 3, seven cameras, 14a-14g, are shown--each
positioned in the y-z plane of the card, at 10 degree spacings.
Additional cameras (not shown) may be positioned in the x-z plane of the
card, with similar angular spacings.

[0050] Desirably, images of the card are captured from a variety of
perspectives. Basically, the idea here is to sample the reflectivity
function of each a-pel on the card from a number of different directions,
and use the sampled data points to determine (i.e., estimate) the
approximate wobble and azimuth angle at which reflectivity is maximum.
The resulting data may be regarded as the 2D (wobble/azimuth) albedo
function across the card. (Note: the scientific literature tends to
explicitly add the phrase "bi-reflectance" or "bi-directional" to the
word "albedo"; most of this disclosure will implicitly include this
directional aspect of the word "albedo".)

[0051] The FIG. 3 arrangement may comprise an array of 15 cameras, in an
"X" configuration, each placed along a hemispherical surface over the
card. Or the depicted arrangement may comprise 49 cameras, in a 7×7
array, warped to fit over the hemispherical surface. Lesser (or greater)
numbers of cameras can alternatively be used (e.g., "X" patterns
employing 5 or 10 cameras, or square arrays of 9 or 16 cameras). A
minimal arrangement may comprise just three or four cameras, e.g., each
viewing the card from an oblique angle of 15 degrees, and spaced every
120 or 90 degrees, respectively, around the object.

[0052] It is not necessary that the cameras all be equi-distant from the
card. Nor is the spacing critical. In typical arrangements, lens-to-card
distances on the order of 3''-30'' inches may be used, although greater
and lesser distances are also possible. (Especially when the card is
imaged from short distances, compensation for parallax effects may be
desirable. For example, the viewing angle for camera 14g may not be 30
degrees for all a-pels across the card. However, this effect is easily
determined and can be taken into account when determining the wobble and
azimuth angles.)

[0053] Nor is it required that the cameras be disposed in a regular array.
Some advantages can accrue by stochastic sampling, i.e., by sampling from
random directions.

[0054] In actual practice, cost and mechanical considerations may dictate
that a lesser number of cameras be used. In one alternative, a single
camera is used, in conjunction with an array of minors. Either the
camera, or the mirror system, is moved as necessary to capture a sequence
of different card images--each from a different direction.

[0055] Yet another arrangement is to position the card on a tip/tilt
table, beneath a single camera. The card can be sequentially moved to a
number of different positions relative to the camera, and an image is
then acquired from each different card-camera presentation angle.

[0056]FIG. 3 does not show an illumination source, and the particular
illumination source used is a secondary matter (i.e., of signal-to-noise
ratios on obtaining wobble/azimuth signature data), but not of primary
concern, where a variety of light sources should all suffice. Ordinary
office lighting can potentially suffice--provided care is taken that the
camera systems do not shadow the card and produce measurement-system
artifacts. Or the apparatus 20 can include one or more controlled light
sources. Generally, lighting from above the card surface is desired.
Diffuse lighting can be used, but may tend to blur the directional
reflectivity of a-pels on the card surface and tend to reduce the wobble
amplitude of the resultant wobble peaks.

[0057] In some arrangements, polarized light, and/or polarizing filters at
the sensors, can be used to further characterize the card's albedo
function. Similarly, the albedo function may be sampled at different
wavelengths of light. Both of these approaches can provide significant
practical extensions of the basic principles of this disclosure, but they
are not necessary for basic enablement.

[0058]FIG. 4 shows the magnitude of light reflected from a particular
a-pel 12a on the card, as sensed by cameras 14a-14g, at respective angles
of -30, -20, -10, 0, 10, 20, and 30 degrees along the y-z plane.

[0059] Light reflected from a given `pel` may be imaged onto a 3×3
patch of pixels in directly-overhead camera 14g, but may be imaged onto
only 2×3 patches of pixels in cameras 14a and 14g. Intervening
cameras 14b, 14c, 14e, and 14f may have fractional rows/columns of
photosensors illuminated by light reflected from the a-pel. With
knowledge of the CCD layout (e.g., the dimensions of each component
photosensor, and the border between photosensors), and the positioning of
the cameras, such effects (e.g., fractional illumination) can be
compensated-for (e.g., by weighting the contributions from different
photosensors differently in aggregating the net illumination reflected
from an a-pel. The aggregate illumination from an a-pel may thus range in
value from zero to 2295 (the latter being a full 8 bit signal of 255,
summed across 9 fully-illumined pixels).) For convenience of notation,
this aggregate is represented in FIG. 4 on a scale of 0-100.

[0060] From inspection (i.e., by imagining a curve connecting the depicted
sample points), it appears that the reflectivity function from sample
a-pel 12a has a peak at about 6 degrees. However, the curve defined by
FIG. 4 is just one slice through the reflectivity function's 3D shape
(wobble/azimuth/magnitude). Other cameras--viewing the a-pel from
positions off the axis of cameras 14a-14g, are needed to more fully
characterize the a-pel's reflectivity function, or at the very least the
general location of the albedo peak. Even with just the data from FIG. 4,
however, we know that the reflectivity function "leans" towards the top
edge of the card. (Unknown, from this data, is whether it leans also
towards the left or right edges of the card.)

[0061] Given sample data from a set of non-collinear viewpoints, a
centroid algorithm can be applied to mathematically determine a maxima of
the a-pel's reflectivity function, in wobble angle, azimuth angle, and
magnitude. This process can be performed by the computer 15 of FIG. 4.
(Computer 15 can also serve other roles, such as being the
"decisionmaker" that adjudicates whether cards sensed by reader 30 are
genuine.)

[0062] A statistical analysis of the wobble angles from different a-pels
across a card is expected to show a generally Gaussian distribution
(though significant departures from true Gaussian should cause no
problem, in any event), centered about zero degrees, and with a standard
deviation on the order of between 1 and 15 degrees, depending on
material.

[0063] In FIG. 3, the cameras span a range of angles, +/-30 degrees, that
is larger than the vast majority of wobble angles. Having at least one
camera on each side of an a-pel's wobble angle helps refine the accuracy
by which the wobble angle can be determined (e.g., by the centroid
algorithm). However, this is not a requirement. For example, samples
taken from cameras at 0, 6 and 12 degrees can nonetheless allow
estimation of a wobble angle of, e.g., 15 or 20 degrees.

[0064] When a driver license is manufactured, e.g., by equipment at a
state Department of Motor Vehicles (DMV) office, or at a central
manufacturing facility, the license desirably is characterized by an
apparatus 20 like that shown in FIGS. 3 and 4 prior to being issued to
the owner (which may be by mailing, in the case of a central
manufacturing facility). In some processes, such apparatus can be
included at the end of the manufacturing process. The resulting data is
stored in the database 17 of FIG. 4.

[0065] In one arrangement, the albedo data is stored as a series of
records, each indexed by the a-pel's respective row and column number. If
each a-pel is 0.5 millimeter on a side, the albedo function for a driver
license may comprise 100 rows by 175 columns of data, or 17,500 a-pels
total. Each record may store the wobble angle for that a-pel, together
with the associated azimuth angle, and also the magnitude.

[0066] More or less data can, of course, be stored. For example, in some
arrangements the magnitude data may not be stored. In another, either the
wobble angle or the azimuth angle may not be stored.

[0067] In still other arrangements, more data is stored. The albedo
function for each a-pel may be described not just by the 3D coordinates
of the endpoints of the vectors 11 shown in FIG. 2, but also by the 3D
volume of the reflectivity function. That is, the light reflected from an
a-pel may be narrowly concentrated along a vector 11 (like a spotlight
function), or it may form a broad volume, with lots of spread about the
vector (like a floodlight function). A slice of a spotlight-like
reflectivity function volume is shown by the dashed curve of FIG. 6; a
slice from a more floodlight-like reflectivity function volume is shown
by the solid line.

[0068] In one arrangement, the raw data from all of the cameras is stored
in the database--characterizing the 3D volume reflectivity function at
different sample angles. In another arrangement, a curve fitting
algorithm is applied to estimate a 3D model of the reflectivity volume
from the sample points, and the parameters of this model can then be
stored. Furthermore, a low-order polynomial fit to the volume can be
removed from the data, leaving only the higher order "unique structure"
as a very subtle form of characterizing the volumes. Such possibilities
tend to go beyond what mass-produced cards such as driver's licenses may
contemplate as a practical matter, and point more toward higher
sensitivity applications such as airport security and the like.

[0069] The database 17 in which the albedo data is stored can comprise the
DMV's existing licensee database, e.g., including name, age, driving
restrictions, photo portrait, etc. Or it can comprise a separate
database.

[0070] Driver licenses are typically encoded with machine-readable
information, such as digital watermarks, bar codes and RFID data. The
information conveyed by the machine-readable data may also be stored in
the database with the albedo measurements, together with other
information, such as a card ID.

[0071] The exemplary card characterization process detailed above is set
forth in the flow chart of FIG. 7.

[0072] After characterization, the license is issued to the user. It then
goes into the user's wallet or purse and begins a life of abuse--being
scraped, worn, washed, etc. Eventually, it is pulled from the wallet and
presented as an ID credential, at a reading station. (The reading station
may be at an airport security checkpoint, at a liquor store, in a police
cruiser, at a building access, etc.)

[0073] Desirably, each reader station is relatively inexpensive, and does
not require much training to operate. One version of a reader station 30
(FIG. 8) is a conventional personal computer 34, equipped with a single
camera 32 and a network connection 36.

[0074] The camera 32 need not be a carefully characterized measuring
instrument; a simple webcam will suffice. One popular web cam is the
Creative "Live Cam Voice" model, which retails for less than $100, and
has a 1.3 megapixel sensor. Others include the Creative "WebCam Live!
Ultra" model (which includes a 1024×768 sensor), and the Logitech
"Quickcam Pro 4000" (which includes a 1280×960 pixel sensor). These
webcams all can capture 30 frames of video per second, at a resolution of
640×480 pixels or higher.

[0075] To present a card 10 for reading, the user simply waves the card in
front of the webcam (as shown by the wavy dashed line in FIG. 8, which
may be termed a "swoop"). The webcam captures multiple frames of image
data depicting the card, e.g., one every 0.033 seconds.

[0076] As the card moves across the webcam sensor's field of view, it
presents different perspectives, i.e., the webcam captures frames of
image data from different angles. Whereas in the card characterization
apparatus 20 of FIG. 3, plural cameras capture several perspectives of
image data from a stationary card, in the reader arrangement 30 of FIG.
8, a single camera captures several perspectives of image data from a
moving card.

[0077] The data acquired by reader station 30 does not compare--in
quality--to that captured by characterization apparatus 20. However, it
is nonetheless more than sufficient--in conjunction with the earlier
acquired information stored in database 17--to discriminate the card from
even "perfect" counterfeits.

[0078] FIGS. 9A, 9B and 9C show a sample sequence of images that may be
captured by reader station webcam 32. (The center of the webcam's field
of view is shown by the dotted +.) In FIG. 9A, the left edge of the card
is further away from the webcam, so appears fore-shortened. The card is
likewise rotated a bit to the left. In FIG. 9B, the card is squarely
presented before the webcam. In FIG. 9C, the right edge of the card is
further away from the webcam, and the card is rotated a bit to the right.

[0079] In FIG. 9B, a frame is captured with the card directly facing the
camera (i.e., the card is oriented with its z-axis passing through the
lens of the webcam). This is not necessary. As long as the front of the
card comes within about 10 to 20 degrees of facing the camera--at some
point during its travel--the card's 2D albedo function may be
satisfactorily estimated.

[0080] (It is not necessary that card be entirely within field of view in
each frame; useful data can be obtained even if only if part of the card
is visible.)

[0081] FIGS. 10A, 10B, and 10C show another sample sequence. Here the card
is not laterally moved past the camera. Instead, it is simply tilted to
different orientations.

[0082] Because the card in FIG. 10 is moved about just a single axis
(i.e., the "tilt" axis in FIG. 1), the image samples acquired by webcam
32 likewise fall along a common axis. Although the card's albedo function
can be estimated with such data, a better estimate is obtained if the
card is moved around both the tip and tilt axis, as it is being waved in
front of the webcam.

[0083] When the card 10 was originally characterized by apparatus 20, the
measurements were taken in a precisely defined geometrical reference
frame, e.g., in which the card was located at a known position relative
to the cameras. The `wave` of the card in front of webcam 32 does not
enjoy this advantage. Nonetheless, the geometry of the `wave` can still
be precisely assessed. (Note: To be a bit more precise, the card will be
presented to the camera across a series of frames, with each frame
occupying a generally unique angular direction of the camera relative to
the perpendicular of the card, thus producing a form of "track" through
angular space, where from a consumer's or user's perspective waving the
card in front of the camera, the term "wave" is a bit more intuitive).

[0084] A watermark carried by the card can play a key role here. The
preferred watermark includes a steganographic calibration (e.g.,
reference or subliminal grid) signal by which affine distortion of the
imaged card can be accurately quantified. (Examples are given, e.g., in
U.S. Pat. Nos. 6,614,914 and 6,580,809; in publications US US20040105569
and US20040101157; U.S. Pat. No. 6,959,098 teaches how distortion can be
characterized by such watermark calibration signals in conjunction with
visible image features.) From this affine distortion information, the 6D
location of the card (x, y, z, tip, tilt, rotation) relative to the
webcam can be determined.

[0085] In processing the frames of image data captured by webcam 32,
computer 34 thus starts by examining each frame for watermark
information, and characterizing the position of the card depicted in such
frame by reference to such information. With this position information,
the angle from which the sensor views each a-pel in each frame can be
determined. (Again, parallax correction may be appropriate.)

[0086] Once each frame of card data is associated with its respective
viewing angles, the reflectivity of different a-pels can be assessed at
different angles--using a procedure like that detailed in conjunction
with apparatus 20. That is, the intensities of reflected light sensed
from a given a-pel--viewed from different perspectives--can be applied to
a centroid algorithm to estimate the wobble and azimuth angles at which
such a-pel reflectivity is maximized. Given that the geometry of
measurement is significantly less controlled than during the production
process, the precise algorithms for estimating wobble peaks and angles is
inherently much noisier but nevertheless still quite valid.

[0087] The resulting "random track sample" of the 2D albedo map for the
card can be sent over the network, and compared against the albedo maps
stored in database 17. Despite the many degradations to which the card
may have been physically subjected since its manufacture and
characterization, the set of albedo data acquired by reader station 30
will correlate, and will correlate strongly, with only one set of albedo
data in the database. The card to which it corresponds establishes its
true identity. This approach represents the complete data version of
authentication, essentially boiling down to sending the database all
captured frames of data (or at least heavily compressed frames).
Practical situations (and generally not-for-free bandwidth considerations
on communication channels) point toward finding data economies at the
camera head which can on the one hand greatly reduce the data volume
required to be sent to the database, while at the same time maintaining
the essential albedo content required for formalized distinguishability
testing processes.

[0088] (The assessment of geometric orientation, and estimation of the 2D
albedo map, can be performed by computer 34, but need not be. In other
arrangements, the raw image data collected by reader 30--or a derivative
thereof--can be transmitted to remote computer 15 for such processing.)

[0089] Given the simplicity of the reader station 30, it is unlikely that
the 2D albedo data it collects will be as accurately, and as finely,
resolved as that produced by apparatus 20. However, such levels of
accuracy and resolution are not required.

[0090] For example, instead of characterizing the reflectivity of each
a-pel's wobble and azimuth angles to two or three significant figures
(e.g., 0-90 degrees and 0-360 degrees), as might be achieved by apparatus
20, a relatively coarser estimate may be made. For example, referring to
vector 11 in FIG. 2, the reading station computer 34 (or computer 15) may
simply quantify the vector as leaning into one of four quadrants: I, II,
III or IV (northeast, northwest, southwest, or southeast). In this
arrangement, each a-pel is associated with just a two-bit datum. This
abbreviated data set can likewise be sent to database 17 for comparison
against the earlier-acquired measurements, e.g., by a Bayesian engine 21.
Again, only one previously-characterized card will highly correlate with
such data. (Sufficient correlation can be determined by reference to a
threshold. Depending on the application, the absolute correlation
coefficient threshold may be set fairly low, e.g. between 0.01 and 0.1 In
other applications, a threshold of between 0.1 and 0.5 may be used. In
still others, a correlation of more than 0.5 may be required.)

[0091] There is nothing magic about quadrants. The reflectivity may be
represented as a single bit (e.g., leans north or south; or leans east or
west). Or it may be represented with higher precision (e.g., falling into
one of eight 45 degree swaths). Etc.

[0092] (Typically, the 2D albedo map acquired by apparatus 20, and stored
in database 17, will be two- to ten-times higher in resolution than the
albedo map data collected at the reader station 30. To perform the
correlation, the finer a-pel data in database 17 can be combined--across
several small a-pels--to yield a vector sum corresponding to a larger
a-pel, of the sort estimated by reader 30.)

[0093] In some embodiments, albedo discrepancies due to the over-sampling
of the data at the time the card is initially characterized (e.g., during
so-called "enrollment" of the card's characteristics in the DMV database,
such as at the time of driver's license issuance) and the relative sparse
sampling when the card is later sensed by a retail terminal, are
mitigated by using less than all of the former data. For example, while
49 different views of the card may have been captured during enrollment
(e.g., from 49 cameras, or by positioning a tip/tilt stage to 49
different positions), a reference albedo may be calculated by providing
to a centroid algorithm only data from a subset of these views, e.g.,
those most closely matching the views captured during the swoop of the
card at the retail presentment. The results of this calculation can then
be correlated with results from a centroid operation performed on data
captured during the swoop. If correlation is found (exceeding some
nominal threshold, such as 2-10%), then the license is deemed to be the
original.

[0094] Put another way, such a method includes capturing plural views of
an original license (or other object)--each from a different perspective,
and storing corresponding data (e.g., at enrollment). Later, plural views
are captured from a suspect license--again, each from a different
perspective. A subset of the originally stored data--corresponding to the
perspectives from which the views of the suspect license were
captured--is then identified (e.g., frames captured at enrollment from
vantage points most similar to those at which swoop image frames were
captured). By reference to this subset, and the subsequently-captured
views, a determination is made as to whether the suspect license is the
original license. (Centroid algorithms can be applied to the subset data,
and to the later-captured views of the suspect license, to determine two
albedo functions. A correlation operation, such as a dot product
operation, can then be performed on these two functions to determine
correspondence.)

[0095] Another approach is to calculate two albedo functions from the
reference data captured at enrollment: the first applying all of the
reference data to a centroid algorithm, and the second using just those
frames closest to the frames captured during the swoop at retail
presentment when computing albedo centroids. The two resulting albedo
functions are compared, e.g., on an a-pel by a-pel basis. Where the two
functions yield a significantly different directional albedo for a
particular a-pel (e.g., exceeding a preset threshold, such as falling in
a different quadrant, or diverging by more than 45 degrees), then that
a-pel can be disregarded when correlating against the data captured
during the swoop at retail presentment. (Still another approach is to use
only those a-pels that are most significantly changed when computed from
a subset of the original data, versus from the unabridged set; i.e.,
disregarding a-pels that match within a threshold.)

[0096] The reader station may provide audio or visual feedback to the
user, to confirm that the user's wave of the card was satisfactory. If
the card didn't move enough, e.g., if it didn't provide image viewpoints
differing by at least a threshold amount (e.g., 5 degrees, 10 degrees, or
20 degrees), feedback might not be provided. If the card was moved so
quickly that too few frames were captured (or the frames were too
blurry), feedback might not be provided Likewise if the card movement was
outside the sensor's field of view too much. If no fault is noted with
the image capture, feedback indicating a proper wave can be provided.

[0097] The data returned by the Bayesian engine 21 can take different
forms. It could simply give a "green light" indication to the reader
station, indicating that the card matched one in database 17. (Since the
2D albedo profile is so unique, details of the match may not be
necessary; there is essentially only one possibility--the card is the one
it purports (e.g., by its text or watermark or barcode) to be.) In other
arrangements, the remote computer 15 can return to the reader station 30
information about the card, or its bearer, obtained from database 17 (or
other database).

[0098] In a particular arrangement, the watermark conveyed by the card is
used not just for geometrical orientation purposes, but is also decoded
by reader station 30 to provide an initial assessment of the card's ID.
That is, it may convey the name of the user, or their driver license
number. This decoded information may be sent to the database 17 with the
albedo data. In this case, the database's task is simplified. It
identifies the card in its storage issued to that user, or with that
driver license number. Then a simple comparison is performed between the
reference albedo map stored for that card, with the albedo map estimate
provided by reader 30. If they correlate, the card is valid. (Other
machine readable data may be used for similar purpose, e.g., bar code,
RFID, etc.)

[0099] (The watermark may be read from an aggregate image, produced by
combining several of the sampled images, after correcting each for affine
distortion. Technology for combining low resolution images by reference
to encoded digital watermark signals, so as to yield a higher quality
image, is taught, e.g., in published U.S. patent application
20030002707.)

[0100] The `wave` of the card in front of the webcam may result in the
capture of 10-30 images, depending on the speed of movement. Generally
speaking, the more images, the better. In some arrangements, however, it
may be desirable to limit the number of images processed, e.g., to a
maximum of 12. In deciding what images to keep, a variety of criteria may
be employed.

[0101] For example, if two images present essentially the same perspective
of the card, then one may be discarded, or at least optimally averaged
into the other taking account of slight affine transformation changes.
Similarly, if any image suffers a technical defect--such as glare or
undue blur, it may be discarded too. (Image sharpness may be estimated by
transforming part or all of a captured frame of image data into the
frequency domain, and determining the amount of high frequency energy).
Images that present the card at a too-oblique angle (e.g., more than 30
or 45 degrees) may also be discarded.

[0102] In an alternative reading arrangement, the card is laid (or held)
stationary, and a camera is waved over it. The camera in such arrangement
may be a cell phone. In this arrangement (as in others), the raw captured
image data can be transmitted to a separate (e.g., remote) computer
device for processing, or it can be processed by the same device used in
the capturing of the data.

[0103]FIG. 12A details one "swoop" pass of a sensor over a card (or a
card in front of a sensor). Each `x` represents the orientation of the
card relative to the sensor at a sample instant. The illustrated plot is
shown in the tip/tilt frame of reference (with 0/0 indicating that the
card's z-axis is passing through the sensor lens).

[0104] At the first sample instant 41, the card is oriented with a tilt of
about 12 degrees, and a tip of about 29 degrees, relative to the sensor.
Subsequent samples are taken at different orientations. At each
orientation, the brightness of the a-pels are sensed.

[0105] The star FIG. 43 in FIG. 12A shows the tip/tilt at which the
reflectivity from a particular a-pel 12a is maximized. At all other
points on the graph, the brightness reflected from this a-pel is less
than the brightness that would be sensed at position 43. By sampling the
intensity of the 2D albedo profile at all the `x` points, however, the
centroid algorithm allows estimation of the location of maxima 43.

[0106] It may be noted that the sample points in FIG. 12A define a
two-part `swoop`--the first going from sample 41 to 45, and the second
going from sample 45 back up to 47. The samples near 45 are relatively
closely spaced, indicating that the sensor (or card) movement is slowing.
The fact that the swoop generally reverses direction indicates that the
sensor (or card) movement similarly generally reverses its movement for
the second part of the swoop.

[0107] (A two-part, generally-reversing, swoop isn't necessary; a one-way,
unitary swoop can also be used. However, the former is preferred. A
unitary swoop generally characterizes the shape of the 2D albedo profile
along just one of its dimensions. The second part of a
generally-reversing swoop (provided it isn't identical to the first part)
provides samples spaced in another dimension of the albedo
profile--allowing the profile to be characterized more accurately.)

[0108] Note that all of the samples in FIG. 12A are on the same side of
maxima 43. This will be the typical case. (Also typical is that the
movement will usually not provide a sample directly at the maxima point
43 for a-pel 12a.) Preferable--although not necessary--is for the second
part of the `swoop` movement to take samples on the opposite side of the
maxima. Such a sampling arrangement in shown in FIG. 12B. By sampling the
2D albedo profile on two sides of its maxima, the shape of the
profile--and thus the location of the maxima--can more accurately be
determined.

[0109] Although the calibration signals steganographically encoded with
the preferred digital watermark are highly useful in determining the
geometry of card-presentation-to-webcam, this geometry can be estimated
by other arrangements. For example, visible features can be identified on
the imaged card (e.g., by pattern matching algorithms), and the
distortion of such features from their known shapes/dimensions can be
used to infer card position. Likewise, if the outer rectangular
dimensions of the card are known (e.g., 2'' and 3.5''), edge-finding
algorithms can be employed to identify the card edges, and these features
can again be used to estimate card orientation relative to the webcam.
(Such arrangements are shown, e.g., in U.S. Pat. No. 6,959,098.)

[0110] Likewise, although the foregoing description did not make use of
watermark data by apparatus 20 to precisely characterize position of the
card, such information is generally helpful and desirably would be used.

[0111] Different a-pels--even adjoining a-pels--on the card may have
entirely different reflectance curves. Such differences can be induced by
the manufacturing arrangement. In an extreme case, the card can be hit
with a meat tenderizing mallet--imparting a marked surface texture to the
card. Other arrangements for making the reflectivity curves relatively
more chaotic can of course be used.

[0112] Reflectance characteristics can also be tailored by choice of
materials. Some materials will generally exhibit relatively diffuse
reflectance characteristics (e.g., floodlight-like 2D albedo profiles).
While such materials can be used, it is preferable to identify materials
that tend to have less-diffuse reflectance attributes, so that the maxima
from each a-pel can more readily be defined.

[0113] In alternative arrangements, each of the oblique card images
captured by apparatus 20 and reading station 30 can be normalized to
their original rectilinear shape and their original scale, prior to
estimation of the 2D albedo map. Again, this can be done by reference to
the watermark calibration information embedded in the card.

[0114] A refinement may be made to the watermark-based image registration
processes described in the cited patent documents, above. Normally, these
processes produce an estimate of parameters that characterize the affine
distortion of an image. The image is then processed to counter-act such
estimated distortion, and the watermark payload is then read.

[0115] This may be refined as follows: instead of using just the original
estimate of the distorting parameters, try perturbing these estimates
slightly. For each perturbed set of estimates, counter-distort the image
accordingly, and sense the strength of the watermark payload signal. It
may be found that counter-distorting with one of these slightly-perturbed
distortion estimates yields a stronger watermark payload signal than
occurs using the original distortion estimate. In such case, the
perturbed estimate more accurately characterizes the distortion.

[0116] By use of such refinement, still more precise determination of card
position/orientation may be achieved (e.g., angular resolution on the
order of a sixtieth of a degree may be obtained).

[0117] The Bayesian engine 21, at one level, simply checks the albedo data
provided from reader station 30 with albedo data corresponding to one or
more cards earlier characterized by apparatus 20 and stored in database
17. One check, as noted, is correlation. This can comprise, e.g.,
computing a dot product between two albedo maps represented in a
zero-mean version. (E.g., each set of albedo data can represent leaning
of the maximum reflectance vector in the east/west dimension (tilt) as -1
for west, and 1 for east. Likewise -1 for north and 1 for south. If there
is no correlation between the albedos, the sum of such products will tend
towards zero. If there is correlation, the prevalence of same-sign
products will cause the sum to increase. This correlation will be
apparent even if 95%-98% of the a-pel reflectivity characteristics are
changed, e.g., by wear, during the card's service life. Those changes
will generally be random; correlation of the remaining 2%-5% will
establish the genuineness of the card.)

[0118] The albedo data sensed for a particular a-pel might also be
processed in connection with a "confidence" factor, e.g., ranging from 1
to 5 (maximum confidence). In the example given above, in which the
sensed albedo "lean" from each pel is quantized as being in one of four
quadrants (I-IV), the confidence factor can be less if the lean is
slight, and more if the lean is great. (More sophisticated confidence
metrics can of course be employed.)

[0119] Table 1 shows the respective quadrant into which each of plural
a-pels "leans":

TABLE-US-00001
TABLE 1
I III III II IV
IV I I II III
I III II IV IV
I II IV I II
III I IV I I

[0121] These confidence factors can be used to bias the weight given each
of the respective a-pel data, in identifying a reference card with the
closest match. Perhaps the simplest biasing function is simply to discard
all of the a-pel data that does not have a confidence of `V.` Such a
filtered set of a-pel data is shown in Table 3:

TABLE-US-00003
TABLE 3
IV
III
III

[0122] Thresholds other than `V` can, of course, be used.

[0123] In slightly more sophisticated arrangements, a-pel data for all
pels having confidence of II or more are used, and the matching algorithm
weights the degree of a match in correspondence with the confidence
factors of the a-pels used in the analysis.

[0124] The Bayesian engine can consider further factors. For example, it
may, over time, learn that certain individuals present their card along a
"swoop" path that seems to have certain consistencies. Detection of a
path following this expected pattern can tend to affirm that the card is
being used by its authorized owner. Marked difference from such an
expected swoop pattern may prompt the reader to have the user repeat the
card presentation, or otherwise focus further inquiry on the user.
Likewise, the Bayesian engine can consider the IP address of the device
sending the data, and factor any inferences therefrom into the analysis.

[0125] In some arrangements, the operation at the database involves
retrieving the albedo data previously stored for a particular card, and
comparing it with data sensed from a reader device--to ensure they
correspond in an expected manner. If so, the card is confirmed to be the
same physical card from which the albedo data was originally measured.
This sequence of operation is used, e.g., when a tentative identification
of the card can be made, e.g., by reference to a name or license number
printed on the card, or encoded thereon in machine-readable form. This
tentative identification is then used to identify one particular set of
albedo data in the database for comparison.

[0126] A more complicated situation arises when no tentative
identification of the card is made before consulting the database. In
this case, the task is to identify a "best match" between the albedo data
derived from data sensed at the reader device, and sets of albedo data
earlier stored in the database.

[0127] Art known from other disciplines can be applied in this
undertaking, such as "robust hashing" art known in audio/video
fingerprinting and elsewhere, and associated database search optimization
techniques. For example, it is not necessary to check the new set of
sensed albedo data against all of the old albedo; certain old data can be
almost immediately excluded from consideration (e.g., by techniques such
as database pruning). The albedo data can be distilled into a smaller
representation, which is robust against many corruption mechanisms. Such
techniques, and other useful technologies, are detailed in WO02/065782,
US20060075237, US20050259819, and US20050141707.

[0129] Different albedo maps can also be characterized for different
spectrums and/or polarizations of illumination.

[0130] The assignee has run tests, using a robot-controlled test jig, at
two discrete angles of tilt in the y direction, covering -10 to 10
degrees at one degree increments in the x-direction. Plural
seemingly-identical demonstration driver licenses of two different
designs have been employed. One license design is particularly
interesting because it is laminated with the 3M Confirm laminate, which
is comprised of little beads, which serve as wobble randomizers.

[0131] The per pixel luminance measurements show consistency between
images captured at a given tilt angle and position on the robot mount.
Also, the luminance measurements vary with tilt angle and position on the
card (pixel number). When a new set of captures are taken of a different
but visually identical card, the per pixel luminance measurements at a
specific tilt angle differ from those of the first card.

[0132] In the arrangements detailed above, the albedo function is
generally static. However, it is possible for the object's albedo
function to be changed (either at the time of initial manufacture, or
subsequently).

[0133] The simplest arrangements allow for the albedo data to be changed
once. Various chemical formations (e.g., photographic emulsions,
photoreactive inks, etc.) change state in response to particular stimuli
(illumination, chemical, thermal, etc.) If a card is provided with such
materials (e.g., on the surface, or embedded within), stimulating same
can induce a change that affects the albedo function.

[0134] One particular arrangement employs a card having photoreactive ink,
illuminated with a laser via a micromirror array (perhaps up to 10-50
million mirrors). By controlling the micromirror orientations, regions of
the card are illuminated, or not, by the laser light. Corresponding
changes are thus induced. (The micromirrors can be controlled so that
laser light exposes some regions for different time periods than
others--further tailoring the change to the albedo function.)

[0135] Another arrangement employs a chemical composition that reacts to
laser illumination at a particular wavelength by producing a broad albedo
peak in the direction from which the illumination is applied. Desirably,
illumination at a different wavelength removes this effect, e.g.,
restoring the surface to a quasi-"virgin" state, or causing a random
albedo response, or a peak in a different direction.

[0136] Yet another arrangement employs a material that changes its optical
index of refraction following exposure to a given chemical compound, such
as water or a solvent. Such a material--spanning the card surface--may be
spritzed with liquid (e.g., with a mist or aerosol spray) to change its
optical properties. Some such materials are described, e.g., in Kim,
Singh and Lyon, "Label-Free Biosensing with Hydrogel Microlenses,"
Angewandte Chemie International Edition, Volume 45, Issue 9, Pages
1446-1449, 2006.

[0137] In each of these arrangements, although only a single state change
is usually possible, several successive generations of data can be
induced by applying the changing mechanism sparingly--changing only a
subset of the a-pels (often a random subset) each time. For example, the
liquid spritzing in the foregoing example may be light enough to alter
just 10% of the a-pels. Even if performed 10 times, further changes may
be subsequently achieved since--statistically--an action that leaves 90%
of the a-pels unchanged, if repeated 10 times, still leaves about 35% of
the pels unchanged. The other change-mechanisms can likewise be applied
to a subset of card features.

[0138] Such techniques can be incorporated in the work flow of a card
issuance system, processing cards either before or after variable data
(e.g., name, photo) are applied.

[0139] Other arrangements allow the albedo function to be changed
virtually without limit. Consider, for example, a card that has a
textured laminate, comprising micro-droplets of clear thermoplastic that
is essentially rigid at temperatures up to about 150 F-250 F, but that
becomes pliable above such temperatures. Such droplets may originally be
uniform in shape (e.g., hemispherical). However, such a card can be
heated to the point the droplets become pliable, and a randomly textured
medium (e.g., plate, roller-wheel, etc.) can then be impressed into the
laminate surface, causing the droplets to deform in random ways. When
cooled, the card will have a radically different albedo profile than
formerly. The process can be repeated as many times as desired. (A
laminate without micro-droplets, but simply comprising a layer of
generally flat thermoplastic material, can similarly be employed.)

[0140] Instead of impressing the laminate with a physical texturing
medium, the laminate may be spot-heated, e.g., using a raster-scanned CO2
laser--pulsed in a random (or a controlled) manner. Temperature
differentials induced by such technique can cause the plastic material to
deform.

[0141] In one particular arrangement, a pulsed laser obliquely illuminates
a laminate having microdroplets, as shown in FIG. 13. By illuminating the
droplets from different directions, different deformities can be induced.
This can be effected by using plural lasers, or with a single laser and a
mirror arrangement (e.g., an electronically-steerable micromirror array).
Or by use of a single laser, and moving the card, etc.

[0142] Instead of illuminating the plastic material from different
directions to yield differently-shaped distortions, the plastic may be
illuminated from the same direction, but for different periods of time.
Other such arrangements will be evident to the artisan.

[0143] Still another arrangement bonds a micromirror array/microlens layer
onto a card substrate. (The lenses can be movable with the mirrors, or
fixed.) Instead of being electronically steered, the micromirrors can
rest on microdroplets of deformable plastic, and point in a direction
dependent on the shape of the respective underlying microdroplet. The
minors can be relative transparent at infrared, allowing emission from a
CO2 laser to heat the droplets of deformable plastic through the minor
elements. By heating the microdroplets from different directions, and/or
for different times, the directions in which the mirrors points can be
varied and controlled. Such a material can be "written" from one angle,
and "erased" from another (and read straight-on).

[0144] Yet another arrangement places a CCD lens array atop a photo resist
layer, on a card. The card can be read from one angle, and written from
another (and read straight-on).

[0145] A point-of-sale terminal can illumine the card at the angle
necessary to read the data.

[0146] In still other arrangements, a card may be re-shaped without
arrangements as elaborate as detailed above. A card may simply be passed
through a feeding mechanism that impresses a shaped roller against its
face. (A simple arrangement is a sand paper-roller.) Even without
elevating the temperature of the card, its albedo function may be
altered.

[0147] Still other arrangements employ intaglio techniques (either inked,
or inkless) to shape the surface of a medium in a desired fashion. Such
techniques are known to the artisan from references such as Deinhammer,
"The Implication of Direct Laser Engraved Intaglio Plates on Banknote
Security," SPIE Vol. 6075, February, 2006, as well as US patent documents
U.S. Pat. No. 6,840,721, 20030145747, 20040025728, 20040232108,
20050072326, 20050115425, 20050139100, 20050193909, and 20060151989, and
international patent publications WO05/002869 and WO06/045128.

[0148] The foregoing and other techniques allow shapes including Morse
topologies to be formed on an object. Morse surfaces can be used to
tailor directional albedo in arbitrary fashions (e.g., by changing the
elevation of topological peaks, changing the position of saddle points,
changing the depths of local depressions, etc.). (C.f. Milton, "Morse
Theory," Princeton University Press, 1963, ISBN 0-691-08008-9; and
Zomorodian, "Topology for Computing," Cambridge Monographs on Applied and
Computational Mathematics, 2005.)

[0149] Metameric inks, whose response decays or changes over time, can be
employed to introduce a temporal variability to the wobble response.
Thermics provide another dimension, varying the outputted response in
response to temperature. Different directional albedo signals may thus be
sensed in different domains, e.g., luminance, red, green, blue,
metameric, etc.

[0150] By such technologies, data densities on the order of up to 10,000
Morse-els per square inch may be achieved (homage to Morse). The
directional albedo (luminance) of each element can represent on the order
of 2-8 bits per data from angle alone. The other dimensions of data
provide still more bandwidth.

[0151] In still other arrangements, the albedo function of a surface is
varied not by application of physical or thermal stimulus, but rather by
electrical or molecular changes that serve to vary local reflection.

[0152] Altering the albedo function of a card can be done each time the
card is involved in a transaction, or only at certain times. A
point-of-sale transaction terminal can include components for reading the
albedo function and for changing the albedo function, so that a
read-modify-reread sequence of operations can be performed. (The data
collected in the `reread` operation can be stored locally or centrally
for reference, e.g., used in a subsequent read operation to verify the
card.)

[0153] The albedo function can also be a function of the ink used to print
the card. For example, pearlescent or metameric inks can be used.
Magnetic inks can also be used to impose some directionality (which may
be random) on the illumination reflectance profile.

[0154] More advanced materials can also be employed, such as "quantum
dots" (semiconductor nanocrystals). Quantum dots are available
commercially from vendors including Evident Technologies (Troy, N.Y.), UT
Dots, Inc. (Savoy, Ill.), and American Dye Source, Inc. (Quebec, Canada).
They can be incorporated, e.g., in bead or dust form, into inks,
plastics, and coatings used on licenses. These materials exhibit a narrow
and customized emission spectrum, with an emission amplitude that is
dependent on excitation wavelength. Such materials have known
applications in anti-counterfeiting. As explained at the Evident
Technologies web site: [0155] Two critical aspects of quantum dots give
them the ability to act as an encrypting device for anti-counterfeiting:
their narrow and specifiable emission peaks, and their excitation
wavelength dependent emission intensity. With these traits, several
different sizes (and therefore emission wavelengths) of dots can be
combined with several different wavelengths of excitation light in order
to create an almost infinite variety of emission spectra. Each of these
spectra correspond to one coding combination, which can be made as
arbitrarily complicated to duplicate as the encoder wishes. This process
works as follows. [0156] Each quantum dot size corresponds to a given
emission peak. If dots with different emission peaks are mixed together
in known quantities, the resulting emission spectrum contains each
emission peak present at some measurable intensity. This intensity will
be dependent on both the quantity of dots present and the excitation
intensity (or intensities, if several sources are used). By fabricating
materials containing predetermined amounts of quantum dots which emit at
arbitrary wavelengths, and then establishing their emission spectra at
arbitrary excitation wavelengths, one can create a "code" based on the
relative intensities of emission peaks. For example, if one combines
equal amounts of 1000 nm, 1500 nm, and 2000 nm emission dots, and excites
them at 800 nm; it would yield a different spectral code than unequal
amounts of 1100 nm, 1600 nm, and 2100 nm emission dots excited at 900 nm.
By changing the number of dots, their individual concentrations, their
emission peaks, or their excitation wavelength, one can create and record
a nearly unlimited variety of different spectral codes which can be
easily inserted into plastic sheaths, inks, dyes, fabric, or paper,
allowing quantum dot anti-counterfeiting encryption to go anywhere.

[0157] In a point of sale terminal that illuminates--with a particular
illumination spectrum--a card having quantum-dots, the resulting emission
peaks can be detected by the terminal and employed as a form of
machine-readable data--just like bar codes, RFIDs, digital watermarks,
etc. The data thus represented can be employed in the various
applications known for such other machine-readable data, including use in
conjunction with other machine-readable data conveyed by the card, in
cryptographic key applications, as a fingerprint, etc.

[0158] One particular arrangement employs several layers of quantum dots,
each layer having different characteristics (e.g., emission spectra). The
layers are separated by (or include) photoreactive layers that can be
made successively transparent by appropriate stimulus.

[0159] From the top layer of quantum dots, a first characteristic spectra
is emitted (a simple example may be pure red light) in response to a
particular illumination. If the photoreactive material beneath (or
around) the first layer of quantum dots is made clear, the quantum dot
illumination also extends down to the buried, second layer. Its different
emission spectra (e.g., blue light) changes the net spectra sensed from
the card. Likewise, if the photoreactive material beneath (or included
in) the second layer of dots is made clear, the quantum dot illumination
extends down to the buried, third layer. Its emission spectra (e.g.,
yellow light) combines with that of the other layers to result in a
third, unique, net emission spectra. The varying emission spectra can be
sensed from the card (e.g., in a simple arrangement, as 8-bit data from
red-/green-/blue-filtered CCD elements), and the resulting data can serve
as a changeable (renewable) key, with well-known cryptographic benefits.

[0160] A similar arrangement can include two layers of quantum dots,
separated by an intervening layer that is originally transparent, but
which can be made relatively opaque by application of stimulus (e.g.,
laser energy in a certain band) thereto. (Or, the photosensitive material
can form part of the layer in which the dots are included, instead of
comprising a separate layer.)

[0161] By arrangements such as the foregoing (which may be combined), the
wobble function of an object may be tailored as desired. Thus, instead of
an uncontrollably random function, a controlled (and optionally
pseudo-random) function may be achieved.

[0162] Exercising control over the wobble function allows known
information-theoretic principles to be applied, enabling the wobble
function to represent a desired payload that can be reliably detected
despite physical corruption of the object and distortion of individual
wobbles.

[0163] One such principle is use of error correcting codes, such as turbo
coding, BCH coding, Reed-Solomon block codes, convolutional codes, etc.
Such techniques rely, e.g., on oversampling, i.e., representing N bits of
payload data as M bits of signal, where M>N. The redundancy inherent
in such arrangements allows errors to be noted and corrected. Such
techniques can also employ likelihood measures--indicating the relative
probability that a given bit has a given value (akin to the confidence
factor tables presented above).

[0164] Another principle that can be brought to bear is predictive
filtering. Such techniques are taught, e.g., in U.S. Pat. Nos. 7,076,082
and 6,614,914. In one particular embodiment, a 3×3 region of a-pels
is considered. In normal media, the wobble of the center a-pel may
normally be expected to be correlated to the wobbles of the 8 surrounding
a-pels. If the vector average of these surrounding a-pels is calculated,
the result can be used as a baseline against which the wobble of the
center a-pel can be judged for variance from this natural mean. By such
technique, signals corresponding to the deliberately-induced wobble
features can be raised out of the "noise" of the (typically lower
frequency) wobble characteristic that may naturally occur in a medium.

[0165] Using the cited techniques, a card having 50,000 virtual a-pels
arrayed across its surface may reliably convey a key code comprising,
e.g., 500-5000 bits or more. Such key codes can be used in myriad known
manners, some of which are detailed in the references cited at the
beginning of this specification.

[0166] One particular application of wobbles is in challenge/response
systems. The goal of such systems is to render useless any knowledge that
an attacker may glean through interception of communications between
parties. This is traditionally accomplished with one-time passwords. One
approach (of many) to the construction and use of one-way passwords is to
use a challenge and response system. Traditionally, three components are
used on the client side of such systems: a base secret, a random
challenge, and a hash/encryption function (or other mathematically
one-way function).

[0167] A challenge is issued by the authenticating party. The client
combines the challenge with the base secret and runs the result through a
one-way function. The resulting output is transmitted (e.g., back to the
authenticating party) for validation. The recipient of the output
performs the same calculation, and compares the calculated and received
results. Through such use of the one-way function, the base secret is
never transmitted in the clear between the parties.

[0168] Employing wobbles, the physical card (or other object) can serve as
the base secret and/or the one-way function. The random challenge can
consist of an instruction to image the card under conditions of specific
illumination, position, etc. A sample authentication scenario may proceed
as follows: [0169] 1. Server issues a challenge to the client (rotation
of token . . . say 45 degrees); [0170] 2. Client communicates the
challenge to the end user ("Hold card at approximately 45 degrees"); user
images the rotated card; [0171] 3. Client reads a watermark from the card
to determine card's rotational alignment, and senses wobble signals;
resulting wobble data is sent to the server; [0172] 4. The server, based
on wobble measurements earlier taken from the card, determines the
wobbles that should be sensed from a card at the specified rotation;
[0173] 5. The server compares the results received from the client,
versus those it calculated; if they correlate as expected, the client is
authenticated.

[0174] It will be recognized that if the wobble data sent from the client
is of a coarse "quadrant" variety (e.g., as explained in connection with
the tables above, wherein the lean of the wobble is identified within one
of four quadrants), then rotating the card even a fraction of a degree
causes certain of the wobble vectors to progress into the next
quadrant--but not others. The server--with its more accurate
quantification of the wobble directions--can accurately model which
wobbles will transition into each quadrant, for any given rotation. But
interception of one coarse wobble signal does not allow an attacker to
predict the signal when the card is slightly rotated. (Of course,
rotating 90 degrees should cause each wobble to progress into the next
quadrant.)

[0175] The just-detailed arrangement requires issuance of a specific
challenge to the user, and requires the user to hold the card in an
appropriate fashion. The "S/Key" challenge and response protocol
(sometimes known as Lamport's scheme, and commonly used as a onetime
password system) eliminates this communication, and instead operates on
succeeding hashes to be created from a common base secret. As one work
has explained: [0176] The [S/Key] technique uses a sequence of hashes,
each computed from the previous one in the sequence. The server stores
the last hash in the sequence. To log on, the client provides the
next-to-last hash in the sequence as a one-time password. The server
takes the client's one-time password, hashes it, and compares it to the
stored hash. Both should match. Then the server replaces the hash in the
client's password entry with the password just provided. In the case of
wobbles, before a card (or other token object) is issued to the user, it
is configured to encode a large number of temporary passwords, all
calculated off the base secret. (Once the passwords are used up, the card
can be disposed of.) Each unique signature calculated from the wobbles is
another one-time use password calculated on the base secret (the
construction of the card).

[0177] At first blush, there may seem to be no significant difference
between the two techniques, as a challenge in the first is equivalent, in
the second, to needing to know which password in the sequence needs to be
submitted to the server for authentication.

[0178] By loosening the definition from "password in sequence" to "an
unused password," then the instructions ("challenge") to the end user
becomes the much simpler "wave the card in front of the camera" set.

[0179] Thus, in the simplest embodiment, the client would pass either all
the observed frames, or calculated wobble vectors, to the server.

[0180] An optimization to this is, at the time of session initiation with
the server, the server transmits all positions (based on the watermark)
that have been used. This allows the client to provide better feedback to
the user during the validation step.

[0181] In embodiments in which a cell phone device (which term is used to
encompass devices such as PDAs, iPhones, Blackberries, etc., whether
communicating over a cell network, or WiFi, or WiMax, or Bluetooth, or
otherwise) is used as an optical sensor, the wobble data thereby acquired
can be used in conjunction with other operations performed by the device.
For example, it can authenticate the cell phone to conduct a particular
transaction, serve to enter a password to gain access to a protected
network domain, authorize use of a user's credit card data, etc.

Authentication Chimes

[0182] Wobbles can be used in conjunction with other technologies to
provide highly counterfeit-resistant articles.

[0183] Consider a driver's license with three types of encoded data. One
is a traditional luminance-based digital watermark. The watermark conveys
steganographic calibration data by which the orientation of the card in 6
dimensions can be assessed, by reference to image data captured from the
card as detailed above. (This mark may convey other information as well.)
Such mark can be formed by any known technology, including printing,
texturing, etc.

[0184] A second type of encoded data is represented (e.g., by digital
watermarking) using chrominance features that are out of gamut for
conventional printing technologies (e.g., they cannot be accurately
reproduced using CMYK colors), or are otherwise not readily reproducible
(e.g., due to the dither or half tone patterns used). Metameric or
pearlescent inks can be used, as can fluorescent inks. When such a
reproduction is imaged, e.g., with a RGB CCD sensor array, the resulting
data differs from that obtained when the original is so-imaged.

[0185] A third type of data is represented using directional albedo, as
described herein.

[0186] The presently-contemplated arrangement uses the first encoded data
to allow the relative position/orientation of the card to be determined.
Once the relevant geometrical reference data is thereby established, the
second and third data are examined for correlation.

[0187] In one particular embodiment, the third data (albedo function) is
random. That is, the license (card) is not deliberately shaped to achieve
a particular albedo function. Instead, the payload represented by the
second data may be deliberately chosen to exhibit desired correlations
with this albedo data (e.g., by overprinting; different regions may be
used to avoid interference).

[0188] The second data in this particular arrangement conveys several
different payloads ("keys"). The division of the data into the different
keys can be arbitrary. One technique is to assign different regions of
the card to different keys. For example, the card surface can be
partitioned into 40 regions, each 0.5''×0.5'', each conveying a
different key (represented, e.g., by an array of a-pels numbering on the
order of 1,000 to 10,000). Of course, in other embodiments different
arrangements can be used--including arrangements in which each region
includes plural non-contiguous areas. (One such arrangement assigns
successive pels to successive ones of the 40 keys, stepping across the
card from the top left corner to the top right corner, and then
continuing in this fashion for succeeding rows. Or, instead of single
a-pels, successive tiles of a-pels can be thus-assigned, such as
5×8 a-pel tiles, or 16×16 a-pel tiles, etc. Still other
divisions can, of course, be imagined.)

[0189] The third data (directional albedo) is virtually segregated into a
like number of keys (in this particular embodiment). The division of the
data into plural keys can follow the same division algorithm as applied
to the second data, or a different arrangement can be employed (e.g., key
#1 in the second data can correspond to chrominance features located in
the upper left corner of the card, whereas key #1 in the third data can
correspond to wobble attributes in the lower right corner of the card).

[0190] To further detail this particular embodiment, imagine that each of
the 40 "keys" represents a 10 bit binary string. In the third data, the
wobble of each a-pel may represent two bits (e.g., leaning east or west,
and leaning north or south). The ensemble of bits thus-represented by
a-pels of key #1 can be mapped to a net 10 bit payload. In the second
data, the chrominance features corresponding key #1 are selected to
encode these same 10 bits. Likewise for each of the other 39 keys.
(Error-correcting representations, such as Reed-Solomon, Turbo, or BCH
coding can be employed, but in other arrangements a noisier data signal
is desired--with errors uncorrected.)

[0191] As before, sensing of the three types of data from the card can be
accomplished by a great variety of different sensors; the optical 2D CCD
sensor in a cell phone is exemplary. The cell phone processor, or a
remote processor, can perform the related data decoding and correlation
operations.

[0192] In this exemplary embodiment, the 10-bits represented by the
wobbles associated with key #1 are correlated with the 10-bits decoded
from the chrominance data associated with key #1. Perfect correlation is
not expected nor required. If the correlation coefficient exceeds a
threshold (e.g., if 7 or 8 of the 10 bit positions match), then a match
of key #1 is found.

[0193] Similar operations are undertaken for the other 39 keys.

[0194] Each time suitable correlation is found between respective keys,
the detector device (e.g., the cell phone) renders a short tone (e.g.,
for a quarter of a second). Several keys may each correspond to the same
tone. Thus, keys 1, 6, 11, 16, 21, 26, 31 and 36 may all correspond to
261 Hz (middle C). Keys 2, 7, 12, 17, 22, 27, 32 and 37 may all
correspond to the E above middle C. Keys 3, 8, 13, 18, 23, 28, 33 and 38
may correspond to the G above middle C; keys 4, 9, 14, 19, 24, 29, 34,
and 39 may correspond to the B-flat above middle C, and keys 5, 10, 15,
20, 25, 30, 35 and 40 may correspond to the C above middle C.

[0195] At any given moment, the sensed 10-bit keys may not all match
within the specified degree of correlation (e.g., due to glare, motion
blur, and other anomalies). However, generally speaking, waving the cell
phone relative to the card should produce a pleasing chord, comprised of
the five notes mentioned above.

[0196] In other arrangements, a lesser number of keys is represented by
the second and third data. For example, just four or five keys may be
represented. Each may correspond to a different one of the above-noted
tones. (They may comprise 10-bit keys, or longer strings, such as 40-80
bit keys.) Moving the cell phone over the card still results in a
distinctive chord that indicates that the card is the original--not a
reproduction.

[0197] In some embodiments, care is taken that each of the keys is
relatively uncorrelated. Thus, the chrominance-represented key #1 should
only match wobble-expressed key #1, not wobble-expressed key #2, etc. In
such embodiments, if a match is found between different keys (e.g.,
chrominance-represented key #1 and wobble-expressed key #4), then a
discordant or minor tone can be introduced (e.g., C sharp or D
flat)--immediately cueing the listener that something is amiss.

[0198] Thus, this particular embodiment operates by processing signals
gleaned from 2D and 3D data structures (chrominance pattern and
directional albedo features) and, if suitable correlations are found, a
distinctive authentication signal is then sensed by the user.
Correlations thus drive an experiential (human) decision engine, rather
than a Bayesian-like automated decision process (although such
technologies can of course be used). While an occasional random
correlation might sometimes be found, the resulting short tone is readily
distinguished from the full chord that characterizes an authentic
license.

[0199] While the third (wobble) data in the foregoing embodiment is
random, this need not be the case. Instead, the card construction can be
deliberately tailored to achieve a desired albedo function, so that
specific keys can be thereby represented.

[0200] Nor is it essential that correspondence between the second
(chrominance) and third (wobble) data be indicated by tones. For example,
graphical feedback can alternatively be employed. In one particular
arrangement, a graphical feature (as disclosed, e.g., in copending
application Ser. No. 11/670,841, filed Feb. 2, 2007) can be presented on
a device display. Extending the tones/chord arrangement, different
graphic primitives can be made to appear--each corresponding to a
different one of plural correlations. In the aggregate, the primitives
form a familiar shape or logo (which may be, e.g., the word VALID). As
the sensor is waved over the object, a shimmering graphic appears on the
display--with different elements appearing and disappearing as respective
correlation thresholds are met and lost.

[0201] The three types of data are described as distinct for expository
convenience. However, two or more of these can be formed by the same
process, and may comprise the same structure. For example, raised-ink
intaglio can be used to shape the surface of the card to tailor the
wobbles, and the particular ink(s) used can form the chrominance signal.
Likewise, the luminance can also be tailored by these inks.

[0202] If information about the optical detector is known a priori, then
this information can be employed advantageously in designing one or more
of the various data structures. For example, if the particular pattern of
sensor elements is known, together with their respective colors, then the
chrominance mark can be designed with this information in mind. In an
exemplary arrangement, one or more metameric inks can be selected and
patterned so that a reproduction of the chrominance signal (using, e.g.,
CMYK inks, and conventional printing dither patterns) cannot faithfully
mimic the signal produced by the sensor in response to the original
chrominance feature--yielding corruption of the second data.

Further Disclosure

[0203] A sample embodiment makes use of the 2-Pi-steradian albedo--to use
the `proper` science phrase--better known as the directional reflectance
profile--for each and every resolution element or local group of
resolution elements on a card. At a reading station, a card is moved in
front of a sensor, presenting the card from different angles, as opposed
to being flatly scanned on a scanner.

[0204] Each square millimeter of the card, for example, has its commonly
understood "grey value," "density," "reflectance," etc. This common
understanding is an approximation to the (spectral)-directional-albedo
profile. Sophisticated models often distinguish between objects which are
illuminated in a diffuse "from all directions" type of lighting source,
and the more special case where an object is being illuminated from a
specific angle or otherwise selectively as a function of angle. The
latter case thus has two forms of directionality: source direction and
reflective direction. The resultant "albedo map" is thus a function of 4
dimensions: the reflectance of a unit of light energy transmitted from a
given 2D direction and detected at a separate 2D direction.

[0205] The distinction between coherent (e.g., laser) versus incoherent
illumination may be included for special situations, but the case of
coherent light brings with it "interference" which modulates these
directional albedo functions at very fine directional scales. In the
present discussion, coherent light illumination isn't considered
(although it can certainly be used in various embodiments). Instead, the
exemplary arrangement focuses on low end cameras in effectively diffuse
illumination situations.

[0206] Another special case in all of this is 3M's retroreflective
technology, which viewed in the above 4D description is the 4D albedo map
where the reflectance is `1` for all 4D points where the first two
coordinates are identical to the second two coordinates, and `0`
everywhere else. No real document or physical system approaches this
ideal.

[0207] In a forensic setting, where lighting can be controlled as to
affect all 2-Pi steradian angles of illumination on an object, and
likewise a suitably distant (say 2 meters away) high-quality camera can
separately take images of the illuminated object from all 2-Pi steradian
angles (independently), an empirical set-up is thus established that can
sample the 4D albedo map for any given object. Practically, one would
need to move a light source to successive given directions relative to
the object, where at each illumination direction the camera is moved
through all of its sampling directions. A mere 32 illumination directions
matched to 32 detection directions gives 1024 high resolution images to
be taken for what amounts to be a fairly coarse sampling of the full 4D
albedo map.

[0208] For most low end camera applications, we can greatly simplify our
forensic lab and the subsequent discussion by either accepting generally
diffuse lighting as the standard illumination mode, or perhaps boil down
illumination to six categories: generally diffuse and five semi-diffuse
from straight-on, up, down, left and right. The six-mode approach should
be adequate for almost all general-low-end-camera applications--possibly
even a bit of overkill.

[0209] So, proposition number one is that in a forensic lab with a good
12-bit grayscale camera sampling at, say, 128 different directions on any
given single illumination condition, identically produced cards will
nevertheless give rise to quite distinguishable albedo maps simply due to
manufacturing processes involved with the stock, printing, laminates,
etc. If this is not the case, it should not negate the overall approach
described here, but it will possibly make it more challenging as an
engineering matter. Be this as it may, albedo map "variational
differences" on the order of at least a few percent if not 5 to 10
percent should be expected and readily detectable. "Variational" refers
to wobbles as a function of read-angle, and is deliberately an informal
and secondary term, where the main point is that the maps are
sufficiently different.

[0210] Assuming the forensic lab albedo map differences are confirmed
across a wide range of examples, this leads to the first test for garden
variety cameras: by waving two identically-produced "regular-old" cards
in front of a camera in a controlled, reproducible way, ensuring at least
a 20 degree read-angle swath, will one card consistently produce a data
set which is distinguishable from the other, where for example 15 frames
of image data are collected? The answer is expected to be `yes,` but it
would not be surprising if the difference was so slight that only
carefully controlled conditions applied multiple times would be necessary
to meet basic distinguishability statistics. The plausibility argument
that there will be meaningful signal gets down to the fact that some ten
or twenty thousand effective locations on the card would be sampled 15
times each, producing a lot of data for one binary decision: same or
different. This baseline scenario ultimately boils down to
straightforward Bayesian decision statistical descriptions.

[0211] How might such an arrangement be hedged? A first line of hedge is
to search for manufacturing methods which enhance the resulting Bayesian
statistics, period. Things as simple as loosening the tolerances on
laminate thicknesses is but one simple and potentially powerful
experiment. Other loosened tolerances, and introduction of random
functions, could similarly be used, alone or in combination--many at low
or no cost (or effecting a cost savings). Skipping ahead, one would hope
that two or three key methods could start to make the Bayesian "swipe
signatures" (if you will) substantially and reliably different from each
other.

[0212] Next up is the hedge-of-hedges, represented in the extreme by such
things as the 3M retroreflective materials. The key concepts here are
"by-design" and some position on the "no-cost to costly scale." The
general game here is to continue to enhance the Bayesian properties,
while now beginning to pay more attention to angular wobble properties
and how they relate to such loose specifications as "minimum 20 degree
angular presentation of the card." Also, alluding to how camera data
needs to be captured, compressed and shipped to some trusted decision
unit, these practical considerations have to be taken into account as
by-design albedo-map properties are created and tested (and obviously
taking into account cost in all its various forms).

[0213] This immediately preceding discussion presumed the "two identical
cards presented to a camera in a reproducible, controlled manner." This
is obviously not how cards will be used, but it was important to
establish the baseline differences between otherwise identically produced
cards.

[0214] So now we move to normal usage. Presumption number two is that kids
to grandmothers can easily be taught (virtually entirely by tactile
experience) to present cards to cameras within some technically defined
specification on distance, angular movement, speed, number of captured
frames, etc. User testing should be able to establish "99% behavioral
bounds" which then become the hard targets that engineers treat as design
gospel and Bayesian constraints. Normal usage will include the six modes
of lighting conditions, the specs of any given camera, the numbers of
frames acquired and the above-defined limits of behavioral bounds.

[0215] A digital watermark, e.g., as detailed in U.S. Pat. Nos. 6,614,914
and 6,947,571, will provide the informational basis for precise 6
dimensional measurement of the movement of a card in front of the camera:
X, Y, Z, pitch, yaw, roll. The basis is thus formed to uniquely determine
how our ten to twenty thousand albedo-beacons travel through space and
which read-angle is being presented to any given frame. We have our guide
to map any given movement back into a card's unique albedo map, forming a
comparison between a live event and a re-enacted trace through a stored,
trusted map.

[0216] At all but an extreme theoretical level, we're at a pretty good
point right here. All grandma may be doing is sending instance after
instance of these ˜20K by 15 albedo swaths back to a trusted
decisionmaker for adjudication. The very low-end nature of the camera
will ensure that these essentially randomly-complicated and very subtle
signatures are quite buried in various noise and distortion soups, a
first hint at what's good for the decisionmaker (because we've already
designed in plenty of signal in the cacophony of noise) and problematic
for the would-be counterfeiter. The allusion to "random" refers to the
idea that the wobbles will be fairly "random about the Lambertian-profile
expectation" in and around the straight-on to 20/30/40 degrees off-angle
directions. The Lambertian-profile is the one you would expect on average
from a normally reflective surface. The general notion at this point is
that this card can be presented thousands of times, each time producing
essentially new data blobs.

[0217] So we next consider the attacker with a well-equipped lab.

[0218] Will such an attacker be able to discover and record the unique
albedo map of a given card, given the possession of the physical card? Of
course . . . they can rig up a comparable forensic lab set-up. The
practical issue gets down to how long does someone need access to a card
in order to gather sufficient forensic data. Certainly longer than the
card-swiping-in-the-pocket waiter at the fancy restaurant; but a
half-minute in the process outlined above, which characterizes the card
at the DMV at the time of its issuance, will do.

[0219] Will a data-tapper be able to tap the unencrypted data blob feed
from hundreds of presentations of the card and slowly be able to recreate
the unique albedo map of the card? Of course, assuming they also are
tapping the watermark-provided 6D swath vector as well, or use some other
form of 6D registration in order to form a stable basis to start
averaging the albedo map. With enough presentations (along with reliable
6D data), the lower frequency albedo map data (wobbles) will begin to
show up.

[0220] So, physical possession of the card, as well as tapping
6D-enabled-hundreds-of-presentations-unencrypted-data-blobs will both
enable sleuthing of the card's albedo maps. Let's call this entity the
"crude-sleuthed-map" or CSM.

[0221] The next question is, given this CSM knowledge, what can the rogue
do with it? Can they physically reproduce a card that sufficiently mimics
the map so as to fall into the industry standard Bayesian decision
statistics (which would be a published standard by a decisionmaker or
decisionmaker classes)?

[0222] Data-wise, they will clearly be able to simulate a low-end camera,
impress the CSM onto that data, package it up and ship it to the
decisionmaker as if they were grandma doing it. They could
pseudo-randomize presentation 6D swaths as well, new instances of camera
noise, even lay down a base layer of a "nearly identical" card data
replete with digital watermarking data, then overlaying the CSM layer.
One can imagine a fair amount of sophistication in simulating the
presentation of a card to a camera, given the CSM. In any event, this one
needs to be clearly flagged as a usage-model dependent attack well worth
fully exploring in each and every situation, market, application,
whatever.

[0223] Certainly there are other kinds of data-domain-only attacks that
need to be defined, elucidated, studied, counter-attacked and catalogued.
For instance, where does threshold attacking of the Bayesian
decisionmaker fit in, if at all? It is unclear if you will ever get a
"yes" in the first place from a decisionmaker if one doesn't have the
card or the CSM, or maybe you get a lucky "yes" every billion tries and
this becomes the seed of a threshold attack? Then there's the whole
question of the security of the decision making methods, systems,
networks, etc., which all seem to fall into application/market specific
cryptographic definition and cataloguing.

[0224] The question of physical reproduction given the CSM is a more
interesting question. Here, the CSM is synonymous with having the card.

[0225] To start with, we've already established in our designing above
that the same relatively high end and sophisticated machine cranking out
card after identical card has no chance of recreating the CSM, even given
knowledge of the CSM. (This latter statement is ultimately a function of
the design methods we settle on and how "pro-active" they are versus
"reactive," but it is a safe presumption that the high end origination
machine will not be able to even come close to reproducing the card's
albedo map even given full knowledge of the CSM).

[0226] So that leaves the option of a specially designed machine that
attempts to not only duplicate the nominal identical design of the card,
but then impress upon it an artificial duplication of the CSM in a way
that does not include additional albedo map wobbles that will throw the
reproduced card's CSM out of the published Bayesian bounds.

[0227] First of all, building such a machine would be an extreme challenge
at many levels, with but one being that the published Bayesian
bounds--that the machine ultimately has to answer to--do not need to be
limited and can evolve. Probably the biggest challenge would be
proactively sculpting the surface properties of a laminate or equivalent,
or some 80-90% of the 20K surface elements that is, to the required
wobbly patterns of the stored CSM. Even if those wobbles are extremely
low frequency and tame, which they generally won't be, it simply is
difficult to conceive of a machine which could do this. Mask-based
etching? Nano-machines? Microsurgery equipment?

[0228] And then there would be the residual albedo-signature noise to
contend with. The original registration of the albedo map of the original
card might presumably also characterize the higher frequency statistical
attributes of the albedo map. The original stored CSM used by the
decisionmaker could capture this data and use various measures as a kind
of a simple "check-sum" on a given read, forcing our miraculous machine
to first understand these properties as part of the CSM dataset, and then
furthermore reproduce these statistics.

[0229] In any event, serious study and cataloguing of potential
CSM-reproducing machines is required. Presumption number three to this
whole approach is that this miraculous machine will, at the very least,
be exceedingly expensive, and better yet essentially beyond the reach of
current and near-term technology.

[0230] So, attack-wise, given knowledge of the CSM, you've got the
datawise simulation of a camera presentation and you've got the
miraculous but at the very least quite expensive CSM-reproducing machine.
Each requires the not so trivial step of gaining knowledge of the CSM.

[0231] Going back to the CSM-reproducing machine, at this point might it
be equated to the mythical three-embedded-room-deep machine at the NSA
which molecularly CATSCANS smart cards in order to sleuth their secrets?
It would not be surprising if a proof is established that the technical
challenges in creating a CSM-reproducing machine are on the same
tall-order scale as creating the machines intended to bust smart cards
and other tamper-proof electronics.

CONCLUDING REMARKS

[0232] This specification covers a lot of ground--much of it new. The
breadth of application of the disclosed technologies is large, as will be
apparent to artisans skilled in the field.

[0233] For example, it will be apparent to artisans that elements of the
disclosed arrangements can be employed in on-line purchasing of goods and
services, and on-line bill paying. Application of pseudo random
cryptographic keys--of the sort represented by, e.g., wobble data--to
such activities are well understood. This is but one of many examples
where the present specification enables novel applications.

[0234] It is expressly contemplated that the technologies, features and
analytical methods detailed in this specification can be incorporated
into the methods/systems detailed in the earlier-referenced documents.
Moreover, the technologies, features, and analytical methods detailed in
those documents can be incorporated into the methods/systems detailed
herein. (It will be recognized that the brief synopses of such prior
documents provided above naturally do not reflect all of the features
found in such disclosures.)

[0235] It will be recognized that elements of the arrangements detailed
herein can be used advantageously in other contexts. For example, while a
directional albedo function has been employed in detailed arrangements,
this function has advantageous utility elsewhere. Conversely, alternative
implementations using technology detailed herein do not need to involve a
directional albedo function.

[0236] More generally, it should be recognized that this specification
discloses a great number of arrangements and included sub-combinations
that are useful and non-obvious apart from the larger embodiments
particularly described. Thus, no particular element or act recited herein
is believed to be essential to definition of patentable subject matter.
Methods and apparatuses in which detailed elements/acts are omitted, or
substituted with other elements/acts, are expressly contemplated. Thus,
by way of example and not limitation, an identity card is not essential
(the detailed embodiments can be practiced, e.g., to identify a
particular physical object, such as a wristwatch); an optical sensor is
not essential (identification can be based on different physical
measurements, such as of acoustical properties); a random track of an
object before a sensor is not essential (a carefully controlled track may
be employed), watermarked data is not essential (e.g., position--if
relevant--can be determined by other means), etc., etc.

[0237] Moreover, novelty does not reside only in the overall system, but
also in subcombinations disclosed herein. For example, the measurement
apparatus of FIG. 3 is believed patentable per se, as is the concept of
uniquely identifying an article by reference to its directional albedo
function, as well as imparting a deliberately random feature to a license
prior to issuance, so too perturbing watermark-estimated orientation data
to generate refined orientation data, and likewise weighting wobble data
in accordance with a confidence factor in determining a match, etc., etc.
(Some such subcombinations are particularly noted in the listing that
follows, although such listing is not exhaustive.)

[0238] Applicants expressly note that results achieved by certain
combinations and subcombinations may be achieved by other
combinations/subcombinations that are straightforward to artisans in the
field--informed by the teaching of this specification. For example, while
this specification teaches that a card may be imparted a random surface
texture by hitting it with a meat tenderizing mallet, the artisan will
immediately recognize that such a result may be achieved by myriad other
straightforward means (e.g., rubbing with sandpaper, laser etching, etc.)

[0239] Arrangements using concepts detailed herein can also make use of
machine-readable technologies (e.g., bar codes, RFIDs, magnetic stripes,
etc.), or can be substituted for such technologies in previously known
arrangements.

[0240] Having described and illustrated various principles of our work by
reference to particular examples, it should be apparent that the detailed
technology can be modified in arrangement and detail without departing
from such principles. Accordingly, we claim all such embodiments as come
within the scope and spirit of the following claims and equivalents
thereto.